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Knowledge existing in modern information systems usually comes from many sources and is mapped in many ways. There is a real need for representing “knowledge pieces” as rather universal objects that should fit to multi-purpose a- ing systems. According to great number of information system’s tasks, knowledge representation is more or less detailed (e.g. some level of its granularity is - sumed). The main goal of this paper is to present chosen aspects of expressing granularity of knowledge implemented in intelligent systems. One of the main r- sons of granularity phenomena is diversification of knowledge sources, therefore the next section is devoted to this issue. 2. Heterogeneous Kno...
ICM 2010 proceedings comprises a four-volume set containing articles based on plenary lectures and invited section lectures, the Abel and Noether lectures, as well as contributions based on lectures delivered by the recipients of the Fields Medal, the Nevanlinna, and Chern Prizes. The first volume will also contain the speeches at the opening and closing ceremonies and other highlights of the Congress.
Annotation The three volume set LNCS 4491/4492/4493 constitutes the refereed proceedings of the 4th International Symposium on Neural Networks, ISNN 2007, held in Nanjing, China in June 2007. The 262 revised long papers and 192 revised short papers presented were carefully reviewed and selected from a total of 1.975 submissions. The papers are organized in topical sections on neural fuzzy control, neural networks for control applications, adaptive dynamic programming and reinforcement learning, neural networks for nonlinear systems modeling, robotics, stability analysis of neural networks, learning and approximation, data mining and feature extraction, chaos and synchronization, neural fuzzy systems, training and learning algorithms for neural networks, neural network structures, neural networks for pattern recognition, SOMs, ICA/PCA, biomedical applications, feedforward neural networks, recurrent neural networks, neural networks for optimization, support vector machines, fault diagnosis/detection, communications and signal processing, image/video processing, and applications of neural networks.
This book mainly introduces the research overview, results, and achievements of “The Fundamental Research for Trustworthy Software”, a major research plan of NSFC. The Plan focuses on four key scientific issues: (i) measurement and modeling of software trustworthiness; (ii) construction and verification of trustworthy software; (iii) evolution and control of trustworthy software; (iv) trusted environment construction and evaluation. This book aims to establish a research framework for fundamental research on trustworthy software by focusing on the trustworthiness of embedded software and network application software, as well as the trustworthiness of software in key application fields in China. This book is intended for researchers who have been following the evolution of and trends in the trustworthy software; the book is also a valuable reference resource for practitioners and scholars at various levels and in various fields.
(Bayreuth University, Germany), Jennie Si (Arizona State University, USA), and Hang Li (MicrosoftResearchAsia, China). Besides the regularsessions andpanels, ISNN 2008 also featured four special sessions focusing on some emerging topics.
This is Volume III of a three volume set constituting the refereed proceedings of the Third International Symposium on Neural Networks, ISNN 2006. 616 revised papers are organized in topical sections on neurobiological analysis, theoretical analysis, neurodynamic optimization, learning algorithms, model design, kernel methods, data preprocessing, pattern classification, computer vision, image and signal processing, system modeling, robotic systems, transportation systems, communication networks, information security, fault detection, financial analysis, bioinformatics, biomedical and industrial applications, and more.
This book constitutes the refereed proceedings of the Second International Conference on Rough Sets and Knowledge Technology, RSKT 2007, held in Toronto, Canada in May 2007 in conjunction with the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2007, both as part of the Joint Rough Set Symposium, JRS 2007.
This book constitutes the proceedings of the International Symposium on Neural N- works (ISNN 2004) held in Dalian, Liaoning, China duringAugust 19–21, 2004. ISNN 2004 received over 800 submissions from authors in ?ve continents (Asia, Europe, North America, South America, and Oceania), and 23 countries and regions (mainland China, Hong Kong, Taiwan, South Korea, Japan, Singapore, India, Iran, Israel, Turkey, Hungary, Poland, Germany, France, Belgium, Spain, UK, USA, Canada, Mexico, - nezuela, Chile, andAustralia). Based on reviews, the Program Committee selected 329 high-quality papers for presentation at ISNN 2004 and publication in the proceedings. The papers are organized into many top...
Personal health and well-being was and is important for all individuals. This includes the way people are living, what they do to stay healthy as well as a profound, well-informed diagnosis and appropriate treatment in case of disease. To achieve these goals, modern medicine is provided with a large variety of tools to assess a patient's health state and collect the information required for a proper diagnosis and treatment, which is tailored to the patient's needs. Many of these available tools use signals either generated by the human body, for example, electroencephalogram (EEG) and electrocardiogram (ECG), or by interacting with the human body while traversing it like microwaves or reflec...
The three-volume set LNCS 6675, 6676 and 6677 constitutes the refereed proceedings of the 8th International Symposium on Neural Networks, ISNN 2011, held in Guilin, China, in May/June 2011. The total of 215 papers presented in all three volumes were carefully reviewed and selected from 651 submissions. The contributions are structured in topical sections on computational neuroscience and cognitive science; neurodynamics and complex systems; stability and convergence analysis; neural network models; supervised learning and unsupervised learning; kernel methods and support vector machines; mixture models and clustering; visual perception and pattern recognition; motion, tracking and object recognition; natural scene analysis and speech recognition; neuromorphic hardware, fuzzy neural networks and robotics; multi-agent systems and adaptive dynamic programming; reinforcement learning and decision making; action and motor control; adaptive and hybrid intelligent systems; neuroinformatics and bioinformatics; information retrieval; data mining and knowledge discovery; and natural language processing.